Pandas Profiling Report

Dataset statistics

Number of variables	24
Number of observations	746
Missing cells	3734
Missing cells (%)	20.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	140.0 KiB
Average record size in memory	192.2 B

Variable types

Numeric	6
Categorical	18

Warnings

`dl_applied` has constant value "D/L"	Constant
`overs` has constant value "20"	Constant
`date` has a high cardinality: 538 distinct values	High cardinality
`player_of_match` has a high cardinality: 223 distinct values	High cardinality
`id` is highly correlated with `season`	High correlation
`season` is highly correlated with `id`	High correlation
`first_bat_score` is highly correlated with `second_bat_score`	High correlation
`second_bat_score` is highly correlated with `first_bat_score`	High correlation
`id` is highly correlated with `season`	High correlation
`season` is highly correlated with `id`	High correlation
`first_bat_score` is highly correlated with `second_bat_score`	High correlation
`second_bat_score` is highly correlated with `first_bat_score`	High correlation
`id` is highly correlated with `season`	High correlation
`season` is highly correlated with `id`	High correlation
`first_bat_score` is highly correlated with `second_bat_score`	High correlation
`second_bat_score` is highly correlated with `first_bat_score`	High correlation
`umpire1` is highly correlated with `team1` and 7 other fields	High correlation
`team1` is highly correlated with `umpire1` and 11 other fields	High correlation
`season` is highly correlated with `umpire1` and 11 other fields	High correlation
`eliminator` is highly correlated with `umpire1` and 13 other fields	High correlation
`team2` is highly correlated with `season` and 6 other fields	High correlation
`first_bowl_team` is highly correlated with `team1` and 10 other fields	High correlation
`id` is highly correlated with `umpire1` and 11 other fields	High correlation
`umpire2` is highly correlated with `umpire1` and 8 other fields	High correlation
`first_bat_team` is highly correlated with `team1` and 9 other fields	High correlation
`second_bat_score` is highly correlated with `eliminator` and 2 other fields	High correlation
`winner` is highly correlated with `team1` and 8 other fields	High correlation
`toss_decision` is highly correlated with `eliminator`	High correlation
`venue` is highly correlated with `umpire1` and 10 other fields	High correlation
`toss_winner` is highly correlated with `team1` and 9 other fields	High correlation
`result` is highly correlated with `umpire1` and 6 other fields	High correlation
`city` is highly correlated with `umpire1` and 10 other fields	High correlation
`first_bat_score` is highly correlated with `eliminator` and 2 other fields	High correlation
`city` has 13 (1.7%) missing values	Missing
`winner` has 12 (1.6%) missing values	Missing
`eliminator` has 738 (98.9%) missing values	Missing
`dl_applied` has 727 (97.5%) missing values	Missing
`win_by_runs` has 410 (55.0%) missing values	Missing
`win_by_wickets` has 348 (46.6%) missing values	Missing
`result` has 734 (98.4%) missing values	Missing
`umpire3` has 744 (99.7%) missing values	Missing
`date` is uniformly distributed	Uniform
`umpire3` is uniformly distributed	Uniform
`id` has unique values	Unique

Reproduction

Analysis started	2021-08-06 20:11:35.782172
Analysis finished	2021-08-06 20:11:51.139903
Duration	15.36 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	746
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	713552

Minimum	335982
Maximum	1178425
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.0 KiB

Quantile statistics

Minimum	335982
5-th percentile	336019.25
Q1	501209.25
median	598048.5
Q3	980984.5
95-th percentile	1175367.75
Maximum	1178425
Range	842443
Interquartile range (IQR)	479775.25

Descriptive statistics

Standard deviation	284541.8848
Coefficient of variation (CV)	0.3987682534
Kurtosis	-1.339679771
Mean	713552
Median Absolute Deviation (MAD)	205839
Skewness	0.3531419385
Sum	532309792
Variance	8.096408419 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
598016	1	0.1%
548381	1	0.1%
1082607	1	0.1%
501239	1	0.1%
1082597	1	0.1%
419161	1	0.1%
981017	1	0.1%
981009	1	0.1%
598001	1	0.1%
729289	1	0.1%
Other values (736)	736	98.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
335982	1	0.1%
335983	1	0.1%
335984	1	0.1%
335985	1	0.1%
335986	1	0.1%
335987	1	0.1%
335988	1	0.1%
335989	1	0.1%
335990	1	0.1%
335991	1	0.1%

Value	Count	Frequency (%)
1178425	1	0.1%
1178424	1	0.1%
1178423	1	0.1%
1178422	1	0.1%
1178421	1	0.1%
1178420	1	0.1%
1178419	1	0.1%
1178418	1	0.1%
1178417	1	0.1%
1178416	1	0.1%

season
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	12
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2013.369973

Minimum	2008
Maximum	2019
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.0 KiB

Quantile statistics

Minimum	2008
5-th percentile	2008
Q1	2011
median	2013
Q3	2016
95-th percentile	2019
Maximum	2019
Range	11
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.326906256
Coefficient of variation (CV)	0.00165240681
Kurtosis	-1.127006194
Mean	2013.369973
Median Absolute Deviation (MAD)	3
Skewness	0.06805433152
Sum	1501974
Variance	11.06830523
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
2013	76	10.2%
2012	74	9.9%
2011	73	9.8%
2010	60	8.0%
2014	60	8.0%
2016	60	8.0%
2018	60	8.0%
2015	59	7.9%
2017	59	7.9%
2008	58	7.8%
Other values (2)	107	14.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2008	58	7.8%
2009	57	7.6%
2010	60	8.0%
2011	73	9.8%
2012	74	9.9%
2013	76	10.2%
2014	60	8.0%
2015	59	7.9%
2016	60	8.0%
2017	59	7.9%

Value	Count	Frequency (%)
2019	50	6.7%
2018	60	8.0%
2017	59	7.9%
2016	60	8.0%
2015	59	7.9%
2014	60	8.0%
2013	76	10.2%
2012	74	9.9%
2011	73	9.8%
2010	60	8.0%

city
Categorical

HIGH CORRELATION
MISSING

Distinct	30
Distinct (%)	4.1%
Missing	13
Missing (%)	1.7%
Memory size	6.0 KiB

Mumbai	99
Kolkata	77
Delhi	73
Bangalore	66
Hyderabad	63
Other values (25)	355

Length

Max length	14
Median length	7
Mean length	7.357435198
Min length	4

Characters and Unicode

Total characters	5393
Distinct characters	40
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mumbai
2nd row	Delhi
3rd row	Mumbai
4th row	Pune
5th row	Mumbai

Common Values

Value	Count	Frequency (%)
Mumbai	99	13.3%
Kolkata	77	10.3%
Delhi	73	9.8%
Bangalore	66	8.8%
Hyderabad	63	8.4%
Chennai	56	7.5%
Chandigarh	54	7.2%
Jaipur	47	6.3%
Pune	38	5.1%
Durban	15	2.0%
Other values (20)	145	19.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
mumbai	99	13.1%
kolkata	77	10.2%
delhi	73	9.6%
bangalore	66	8.7%
hyderabad	63	8.3%
chennai	56	7.4%
chandigarh	54	7.1%
jaipur	47	6.2%
pune	38	5.0%
durban	15	2.0%
Other values (24)	169	22.3%

Most occurring characters

Value	Count	Frequency (%)
a	923	17.1%
i	389	7.2%
n	386	7.2%
e	374	6.9%
r	319	5.9%
h	303	5.6%
u	272	5.0%
l	250	4.6%
b	221	4.1%
d	216	4.0%
Other values (30)	1740	32.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4612	85.5%
Uppercase Letter	757	14.0%
Space Separator	24	0.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	923	20.0%
i	389	8.4%
n	386	8.4%
e	374	8.1%
r	319	6.9%
h	303	6.6%
u	272	5.9%
l	250	5.4%
b	221	4.8%
d	216	4.7%
Other values (13)	959	20.8%

Uppercase Letter

Value	Count	Frequency (%)
C	136	18.0%
D	104	13.7%
M	99	13.1%
K	89	11.8%
B	81	10.7%
H	63	8.3%
J	55	7.3%
P	45	5.9%
R	23	3.0%
A	19	2.5%
Other values (6)	43	5.7%

Space Separator

Value	Count	Frequency (%)
	24	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5369	99.6%
Common	24	0.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	923	17.2%
i	389	7.2%
n	386	7.2%
e	374	7.0%
r	319	5.9%
h	303	5.6%
u	272	5.1%
l	250	4.7%
b	221	4.1%
d	216	4.0%
Other values (29)	1716	32.0%

Common

Value	Count	Frequency (%)
	24	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5393	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	923	17.1%
i	389	7.2%
n	386	7.2%
e	374	6.9%
r	319	5.9%
h	303	5.6%
u	272	5.0%
l	250	4.6%
b	221	4.1%
d	216	4.0%
Other values (30)	1740	32.3%

date
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	538
Distinct (%)	72.1%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

2011-04-09	2
2010-03-21	2
2008-05-25	2
2014-05-07	2
2017-04-28	2
Other values (533)	736

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	7460
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	330 ?
Unique (%)	44.2%

Sample

1st row	2010-04-24
2nd row	2010-03-29
3rd row	2008-05-16
4th row	2016-04-22
5th row	2010-04-22

Common Values

Value	Count	Frequency (%)
2011-04-09	2	0.3%
2010-03-21	2	0.3%
2008-05-25	2	0.3%
2014-05-07	2	0.3%
2017-04-28	2	0.3%
2011-04-15	2	0.3%
2009-05-05	2	0.3%
2010-03-20	2	0.3%
2017-04-15	2	0.3%
2008-05-24	2	0.3%
Other values (528)	726	97.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2011-04-09	2	0.3%
2010-03-21	2	0.3%
2008-05-25	2	0.3%
2014-05-07	2	0.3%
2017-04-28	2	0.3%
2011-04-15	2	0.3%
2009-05-05	2	0.3%
2010-03-20	2	0.3%
2017-04-15	2	0.3%
2008-05-24	2	0.3%
Other values (528)	726	97.3%

Most occurring characters

Value	Count	Frequency (%)
0	1936	26.0%
-	1492	20.0%
2	1136	15.2%
1	1069	14.3%
4	500	6.7%
5	469	6.3%
3	212	2.8%
8	193	2.6%
9	185	2.5%
7	140	1.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5968	80.0%
Dash Punctuation	1492	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1936	32.4%
2	1136	19.0%
1	1069	17.9%
4	500	8.4%
5	469	7.9%
3	212	3.6%
8	193	3.2%
9	185	3.1%
7	140	2.3%
6	128	2.1%

Dash Punctuation

Value	Count	Frequency (%)
-	1492	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	7460	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1936	26.0%
-	1492	20.0%
2	1136	15.2%
1	1069	14.3%
4	500	6.7%
5	469	6.3%
3	212	2.8%
8	193	2.6%
9	185	2.5%
7	140	1.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7460	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1936	26.0%
-	1492	20.0%
2	1136	15.2%
1	1069	14.3%
4	500	6.7%
5	469	6.3%
3	212	2.8%
8	193	2.6%
9	185	2.5%
7	140	1.9%

team1
Categorical

HIGH CORRELATION

Distinct	15
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

Royal Challengers Bangalore	97
Chennai Super Kings	89
Kolkata Knight Riders	85
Mumbai Indians	84
Kings XI Punjab	84
Other values (10)	307

Length

Max length	27
Median length	16
Mean length	18.16756032
Min length	13

Characters and Unicode

Total characters	13553
Distinct characters	37
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Royal Challengers Bangalore
2nd row	Delhi Daredevils
3rd row	Mumbai Indians
4th row	Rising Pune Supergiants
5th row	Chennai Super Kings

Common Values

Value	Count	Frequency (%)
Royal Challengers Bangalore	97	13.0%
Chennai Super Kings	89	11.9%
Kolkata Knight Riders	85	11.4%
Mumbai Indians	84	11.3%
Kings XI Punjab	84	11.3%
Delhi Daredevils	83	11.1%
Rajasthan Royals	66	8.8%
Sunrisers Hyderabad	53	7.1%
Deccan Chargers	39	5.2%
Pune Warriors	23	3.1%
Other values (5)	43	5.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kings	173	9.3%
royal	97	5.2%
bangalore	97	5.2%
challengers	97	5.2%
delhi	89	4.8%
super	89	4.8%
chennai	89	4.8%
knight	85	4.6%
riders	85	4.6%
kolkata	85	4.6%
Other values (22)	882	47.2%

Most occurring characters

Value	Count	Frequency (%)
a	1525	11.3%
	1122	8.3%
n	1121	8.3%
e	1058	7.8%
i	919	6.8%
s	879	6.5%
r	801	5.9%
l	724	5.3%
g	519	3.8%
h	472	3.5%
Other values (27)	4413	32.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10479	77.3%
Uppercase Letter	1952	14.4%
Space Separator	1122	8.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1525	14.6%
n	1121	10.7%
e	1058	10.1%
i	919	8.8%
s	879	8.4%
r	801	7.6%
l	724	6.9%
g	519	5.0%
h	472	4.5%
o	391	3.7%
Other values (11)	2070	19.8%

Uppercase Letter

Value	Count	Frequency (%)
K	357	18.3%
R	328	16.8%
C	231	11.8%
D	211	10.8%
I	168	8.6%
S	156	8.0%
P	121	6.2%
B	97	5.0%
M	84	4.3%
X	84	4.3%
Other values (5)	115	5.9%

Space Separator

Value	Count	Frequency (%)
	1122	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12431	91.7%
Common	1122	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1525	12.3%
n	1121	9.0%
e	1058	8.5%
i	919	7.4%
s	879	7.1%
r	801	6.4%
l	724	5.8%
g	519	4.2%
h	472	3.8%
o	391	3.1%
Other values (26)	4022	32.4%

Common

Value	Count	Frequency (%)
	1122	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13553	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1525	11.3%
	1122	8.3%
n	1121	8.3%
e	1058	7.8%
i	919	6.8%
s	879	6.5%
r	801	5.9%
l	724	5.3%
g	519	3.8%
h	472	3.5%
Other values (27)	4413	32.6%

team2
Categorical

HIGH CORRELATION

Distinct	15
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

Mumbai Indians	99
Kolkata Knight Riders	91
Kings XI Punjab	90
Royal Challengers Bangalore	82
Rajasthan Royals	80
Other values (10)	304

Length

Max length	27
Median length	16
Mean length	17.88739946
Min length	13

Characters and Unicode

Total characters	13344
Distinct characters	37
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Deccan Chargers
2nd row	Kolkata Knight Riders
3rd row	Kolkata Knight Riders
4th row	Royal Challengers Bangalore
5th row	Deccan Chargers

Common Values

Value	Count	Frequency (%)
Mumbai Indians	99	13.3%
Kolkata Knight Riders	91	12.2%
Kings XI Punjab	90	12.1%
Royal Challengers Bangalore	82	11.0%
Rajasthan Royals	80	10.7%
Delhi Daredevils	78	10.5%
Chennai Super Kings	71	9.5%
Sunrisers Hyderabad	52	7.0%
Deccan Chargers	36	4.8%
Pune Warriors	23	3.1%
Other values (5)	44	5.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kings	161	8.7%
indians	99	5.4%
mumbai	99	5.4%
knight	91	4.9%
riders	91	4.9%
kolkata	91	4.9%
xi	90	4.9%
punjab	90	4.9%
delhi	85	4.6%
challengers	82	4.4%
Other values (22)	870	47.1%

Most occurring characters

Value	Count	Frequency (%)
a	1538	11.5%
	1103	8.3%
n	1099	8.2%
e	965	7.2%
i	926	6.9%
s	892	6.7%
r	745	5.6%
l	676	5.1%
g	484	3.6%
h	452	3.4%
Other values (27)	4464	33.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10302	77.2%
Uppercase Letter	1939	14.5%
Space Separator	1103	8.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1538	14.9%
n	1099	10.7%
e	965	9.4%
i	926	9.0%
s	892	8.7%
r	745	7.2%
l	676	6.6%
g	484	4.7%
h	452	4.4%
u	388	3.8%
Other values (11)	2137	20.7%

Uppercase Letter

Value	Count	Frequency (%)
K	357	18.4%
R	349	18.0%
D	199	10.3%
C	196	10.1%
I	189	9.7%
S	139	7.2%
P	129	6.7%
M	99	5.1%
X	90	4.6%
B	82	4.2%
Other values (5)	110	5.7%

Space Separator

Value	Count	Frequency (%)
	1103	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12241	91.7%
Common	1103	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1538	12.6%
n	1099	9.0%
e	965	7.9%
i	926	7.6%
s	892	7.3%
r	745	6.1%
l	676	5.5%
g	484	4.0%
h	452	3.7%
u	388	3.2%
Other values (26)	4076	33.3%

Common

Value	Count	Frequency (%)
	1103	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13344	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1538	11.5%
	1103	8.3%
n	1099	8.2%
e	965	7.2%
i	926	6.9%
s	892	6.7%
r	745	5.6%
l	676	5.1%
g	484	3.6%
h	452	3.4%
Other values (27)	4464	33.5%

toss_winner
Categorical

HIGH CORRELATION

Distinct	15
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

Mumbai Indians	95
Kolkata Knight Riders	91
Chennai Super Kings	87
Kings XI Punjab	80
Royal Challengers Bangalore	80
Other values (10)	313

Length

Max length	27
Median length	16
Mean length	17.89678284
Min length	13

Characters and Unicode

Total characters	13351
Distinct characters	37
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Deccan Chargers
2nd row	Delhi Daredevils
3rd row	Mumbai Indians
4th row	Rising Pune Supergiants
5th row	Chennai Super Kings

Common Values

Value	Count	Frequency (%)
Mumbai Indians	95	12.7%
Kolkata Knight Riders	91	12.2%
Chennai Super Kings	87	11.7%
Kings XI Punjab	80	10.7%
Royal Challengers Bangalore	80	10.7%
Delhi Daredevils	80	10.7%
Rajasthan Royals	79	10.6%
Sunrisers Hyderabad	46	6.2%
Deccan Chargers	43	5.8%
Pune Warriors	20	2.7%
Other values (5)	45	6.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kings	167	9.0%
mumbai	95	5.1%
indians	95	5.1%
knight	91	4.9%
riders	91	4.9%
kolkata	91	4.9%
delhi	89	4.8%
chennai	87	4.7%
super	87	4.7%
xi	80	4.3%
Other values (22)	878	47.4%

Most occurring characters

Value	Count	Frequency (%)
a	1530	11.5%
	1105	8.3%
n	1104	8.3%
e	994	7.4%
i	932	7.0%
s	886	6.6%
r	746	5.6%
l	676	5.1%
g	487	3.6%
h	477	3.6%
Other values (27)	4414	33.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10315	77.3%
Uppercase Letter	1931	14.5%
Space Separator	1105	8.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1530	14.8%
n	1104	10.7%
e	994	9.6%
i	932	9.0%
s	886	8.6%
r	746	7.2%
l	676	6.6%
g	487	4.7%
h	477	4.6%
u	377	3.7%
Other values (11)	2106	20.4%

Uppercase Letter

Value	Count	Frequency (%)
K	365	18.9%
R	342	17.7%
C	219	11.3%
D	212	11.0%
I	175	9.1%
S	146	7.6%
P	113	5.9%
M	95	4.9%
X	80	4.1%
B	80	4.1%
Other values (5)	104	5.4%

Space Separator

Value	Count	Frequency (%)
	1105	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12246	91.7%
Common	1105	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1530	12.5%
n	1104	9.0%
e	994	8.1%
i	932	7.6%
s	886	7.2%
r	746	6.1%
l	676	5.5%
g	487	4.0%
h	477	3.9%
u	377	3.1%
Other values (26)	4037	33.0%

Common

Value	Count	Frequency (%)
	1105	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13351	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1530	11.5%
	1105	8.3%
n	1104	8.3%
e	994	7.4%
i	932	7.0%
s	886	6.6%
r	746	5.6%
l	676	5.1%
g	487	3.6%
h	477	3.6%
Other values (27)	4414	33.1%

toss_decision
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

field	457
bat	289

Length

Max length	5
Median length	5
Mean length	4.225201072
Min length	3

Characters and Unicode

Total characters	3152
Distinct characters	8
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	bat
2nd row	bat
3rd row	field
4th row	field
5th row	bat

Common Values

Value	Count	Frequency (%)
field	457	61.3%
bat	289	38.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
field	457	61.3%
bat	289	38.7%

Most occurring characters

Value	Count	Frequency (%)
f	457	14.5%
i	457	14.5%
e	457	14.5%
l	457	14.5%
d	457	14.5%
b	289	9.2%
a	289	9.2%
t	289	9.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3152	100.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
f	457	14.5%
i	457	14.5%
e	457	14.5%
l	457	14.5%
d	457	14.5%
b	289	9.2%
a	289	9.2%
t	289	9.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3152	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
f	457	14.5%
i	457	14.5%
e	457	14.5%
l	457	14.5%
d	457	14.5%
b	289	9.2%
a	289	9.2%
t	289	9.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3152	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
f	457	14.5%
i	457	14.5%
e	457	14.5%
l	457	14.5%
d	457	14.5%
b	289	9.2%
a	289	9.2%
t	289	9.2%

winner
Categorical

HIGH CORRELATION
MISSING

Distinct	15
Distinct (%)	2.0%
Missing	12
Missing (%)	1.6%
Memory size	6.0 KiB

Mumbai Indians	104
Chennai Super Kings	99
Kolkata Knight Riders	91
Royal Challengers Bangalore	82
Kings XI Punjab	79
Other values (10)	279

Length

Max length	27
Median length	16
Mean length	18.09673025
Min length	13

Characters and Unicode

Total characters	13283
Distinct characters	37
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Royal Challengers Bangalore
2nd row	Delhi Daredevils
3rd row	Mumbai Indians
4th row	Royal Challengers Bangalore
5th row	Chennai Super Kings

Common Values

Value	Count	Frequency (%)
Mumbai Indians	104	13.9%
Chennai Super Kings	99	13.3%
Kolkata Knight Riders	91	12.2%
Royal Challengers Bangalore	82	11.0%
Kings XI Punjab	79	10.6%
Rajasthan Royals	73	9.8%
Delhi Daredevils	67	9.0%
Sunrisers Hyderabad	57	7.6%
Deccan Chargers	29	3.9%
Gujarat Lions	13	1.7%
Other values (5)	40	5.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kings	178	9.7%
mumbai	104	5.7%
indians	104	5.7%
super	99	5.4%
chennai	99	5.4%
kolkata	91	4.9%
knight	91	4.9%
riders	91	4.9%
bangalore	82	4.5%
challengers	82	4.5%
Other values (22)	819	44.5%

Most occurring characters

Value	Count	Frequency (%)
a	1506	11.3%
n	1147	8.6%
	1106	8.3%
e	969	7.3%
i	948	7.1%
s	875	6.6%
r	726	5.5%
l	646	4.9%
g	492	3.7%
h	454	3.4%
Other values (27)	4414	33.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10258	77.2%
Uppercase Letter	1919	14.4%
Space Separator	1106	8.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1506	14.7%
n	1147	11.2%
e	969	9.4%
i	948	9.2%
s	875	8.5%
r	726	7.1%
l	646	6.3%
g	492	4.8%
h	454	4.4%
u	400	3.9%
Other values (11)	2095	20.4%

Uppercase Letter

Value	Count	Frequency (%)
K	372	19.4%
R	334	17.4%
C	217	11.3%
I	183	9.5%
S	171	8.9%
D	170	8.9%
P	106	5.5%
M	104	5.4%
B	82	4.3%
X	79	4.1%
Other values (5)	101	5.3%

Space Separator

Value	Count	Frequency (%)
	1106	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12177	91.7%
Common	1106	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1506	12.4%
n	1147	9.4%
e	969	8.0%
i	948	7.8%
s	875	7.2%
r	726	6.0%
l	646	5.3%
g	492	4.0%
h	454	3.7%
u	400	3.3%
Other values (26)	4014	33.0%

Common

Value	Count	Frequency (%)
	1106	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13283	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1506	11.3%
n	1147	8.6%
	1106	8.3%
e	969	7.3%
i	948	7.1%
s	875	6.6%
r	726	5.5%
l	646	4.9%
g	492	3.7%
h	454	3.4%
Other values (27)	4414	33.2%

eliminator
Categorical

HIGH CORRELATION
MISSING

Distinct	6
Distinct (%)	75.0%
Missing	738
Missing (%)	98.9%
Memory size	6.0 KiB

Rajasthan Royals	2
Kings XI Punjab	2
Mumbai Indians	1
Royal Challengers Bangalore	1
Delhi Capitals	1

Length

Max length	27
Median length	15.5
Mean length	17
Min length	14

Characters and Unicode

Total characters	136
Distinct characters	30
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	50.0%

Sample

1st row	Kings XI Punjab
2nd row	Royal Challengers Bangalore
3rd row	Rajasthan Royals
4th row	Sunrisers Hyderabad
5th row	Delhi Capitals

Common Values

Value	Count	Frequency (%)
Rajasthan Royals	2	0.3%
Kings XI Punjab	2	0.3%
Mumbai Indians	1	0.1%
Royal Challengers Bangalore	1	0.1%
Delhi Capitals	1	0.1%
Sunrisers Hyderabad	1	0.1%
(Missing)	738	98.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
kings	2	10.5%
rajasthan	2	10.5%
punjab	2	10.5%
xi	2	10.5%
royals	2	10.5%
sunrisers	1	5.3%
bangalore	1	5.3%
hyderabad	1	5.3%
indians	1	5.3%
challengers	1	5.3%
Other values (4)	4	21.1%

Most occurring characters

Value	Count	Frequency (%)
a	20	14.7%
n	11	8.1%
s	11	8.1%
	11	8.1%
l	8	5.9%
i	7	5.1%
e	6	4.4%
R	5	3.7%
r	5	3.7%
g	4	2.9%
Other values (20)	48	35.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	104	76.5%
Uppercase Letter	21	15.4%
Space Separator	11	8.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	20	19.2%
n	11	10.6%
s	11	10.6%
l	8	7.7%
i	7	6.7%
e	6	5.8%
r	5	4.8%
g	4	3.8%
u	4	3.8%
j	4	3.8%
Other values (8)	24	23.1%

Uppercase Letter

Value	Count	Frequency (%)
R	5	23.8%
I	3	14.3%
K	2	9.5%
X	2	9.5%
P	2	9.5%
C	2	9.5%
B	1	4.8%
S	1	4.8%
H	1	4.8%
D	1	4.8%

Space Separator

Value	Count	Frequency (%)
	11	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	125	91.9%
Common	11	8.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	20	16.0%
n	11	8.8%
s	11	8.8%
l	8	6.4%
i	7	5.6%
e	6	4.8%
R	5	4.0%
r	5	4.0%
g	4	3.2%
u	4	3.2%
Other values (19)	44	35.2%

Common

Value	Count	Frequency (%)
	11	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	136	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	20	14.7%
n	11	8.1%
s	11	8.1%
	11	8.1%
l	8	5.9%
i	7	5.1%
e	6	4.4%
R	5	3.7%
r	5	3.7%
g	4	2.9%
Other values (20)	48	35.3%

dl_applied
Categorical

CONSTANT
MISSING
REJECTED

Distinct	1
Distinct (%)	5.3%
Missing	727
Missing (%)	97.5%
Memory size	6.0 KiB

D/L	19

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	57
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	D/L
2nd row	D/L
3rd row	D/L
4th row	D/L
5th row	D/L

Common Values

Value	Count	Frequency (%)
D/L	19	2.5%
(Missing)	727	97.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
d/l	19	100.0%

Most occurring characters

Value	Count	Frequency (%)
D	19	33.3%
/	19	33.3%
L	19	33.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	38	66.7%
Other Punctuation	19	33.3%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
D	19	50.0%
L	19	50.0%

Other Punctuation

Value	Count	Frequency (%)
/	19	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	38	66.7%
Common	19	33.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
D	19	50.0%
L	19	50.0%

Common

Value	Count	Frequency (%)
/	19	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	57	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
D	19	33.3%
/	19	33.3%
L	19	33.3%

win_by_runs
Real number (ℝ_≥0)

MISSING

Distinct	88
Distinct (%)	26.2%
Missing	410
Missing (%)	55.0%
Infinite	0
Infinite (%)	0.0%
Mean	29.88392857

Minimum	1
Maximum	146
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.0 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	11
median	22
Q3	39
95-th percentile	86
Maximum	146
Range	145
Interquartile range (IQR)	28

Descriptive statistics

Standard deviation	27.27682704
Coefficient of variation (CV)	0.9127590762
Kurtosis	3.448360412
Mean	29.88392857
Median Absolute Deviation (MAD)	13
Skewness	1.757294972
Sum	10041
Variance	744.0252932
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
14	13	1.7%
4	11	1.5%
10	11	1.5%
9	9	1.2%
13	9	1.2%
23	9	1.2%
7	9	1.2%
1	9	1.2%
22	9	1.2%
15	9	1.2%
Other values (78)	238	31.9%
(Missing)	410	55.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	9	1.2%
2	7	0.9%
3	5	0.7%
4	11	1.5%
5	6	0.8%
6	7	0.9%
7	9	1.2%
8	5	0.7%
9	9	1.2%
10	11	1.5%

Value	Count	Frequency (%)
146	1	0.1%
144	1	0.1%
140	1	0.1%
138	1	0.1%
130	1	0.1%
118	1	0.1%
111	1	0.1%
105	1	0.1%
102	1	0.1%
98	1	0.1%

win_by_wickets
Real number (ℝ_≥0)

MISSING

Distinct	10
Distinct (%)	2.5%
Missing	348
Missing (%)	46.6%
Infinite	0
Infinite (%)	0.0%
Mean	6.251256281

Minimum	1
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.0 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	5
median	6
Q3	8
95-th percentile	9
Maximum	10
Range	9
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	1.821280843
Coefficient of variation (CV)	0.2913463728
Kurtosis	-0.2611319693
Mean	6.251256281
Median Absolute Deviation (MAD)	1
Skewness	-0.1604678764
Sum	2488
Variance	3.317063909
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
6	82	11.0%
7	79	10.6%
5	70	9.4%
8	54	7.2%
4	40	5.4%
9	36	4.8%
3	18	2.4%
10	11	1.5%
2	5	0.7%
1	3	0.4%
(Missing)	348	46.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	3	0.4%
2	5	0.7%
3	18	2.4%
4	40	5.4%
5	70	9.4%
6	82	11.0%
7	79	10.6%
8	54	7.2%
9	36	4.8%
10	11	1.5%

Value	Count	Frequency (%)
10	11	1.5%
9	36	4.8%
8	54	7.2%
7	79	10.6%
6	82	11.0%
5	70	9.4%
4	40	5.4%
3	18	2.4%
2	5	0.7%
1	3	0.4%

result
Categorical

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	16.7%
Missing	734
Missing (%)	98.4%
Memory size	6.0 KiB

tie	8
no result	4

Length

Max length	9
Median length	3
Mean length	5
Min length	3

Characters and Unicode

Total characters	60
Distinct characters	10
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	no result
2nd row	tie
3rd row	no result
4th row	no result
5th row	no result

Common Values

Value	Count	Frequency (%)
tie	8	1.1%
no result	4	0.5%
(Missing)	734	98.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
tie	8	50.0%
result	4	25.0%
no	4	25.0%

Most occurring characters

Value	Count	Frequency (%)
e	12	20.0%
t	12	20.0%
i	8	13.3%
n	4	6.7%
o	4	6.7%
	4	6.7%
r	4	6.7%
s	4	6.7%
u	4	6.7%
l	4	6.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	56	93.3%
Space Separator	4	6.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	12	21.4%
t	12	21.4%
i	8	14.3%
n	4	7.1%
o	4	7.1%
r	4	7.1%
s	4	7.1%
u	4	7.1%
l	4	7.1%

Space Separator

Value	Count	Frequency (%)
	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	56	93.3%
Common	4	6.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	12	21.4%
t	12	21.4%
i	8	14.3%
n	4	7.1%
o	4	7.1%
r	4	7.1%
s	4	7.1%
u	4	7.1%
l	4	7.1%

Common

Value	Count	Frequency (%)
	4	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	60	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	12	20.0%
t	12	20.0%
i	8	13.3%
n	4	6.7%
o	4	6.7%
	4	6.7%
r	4	6.7%
s	4	6.7%
u	4	6.7%
l	4	6.7%

overs
Categorical

CONSTANT
REJECTED

Distinct	1
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

20	746

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	1492
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	20
2nd row	20
3rd row	20
4th row	20
5th row	20

Common Values

Value	Count	Frequency (%)
20	746	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
20	746	100.0%

Most occurring characters

Value	Count	Frequency (%)
2	746	50.0%
0	746	50.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1492	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	746	50.0%
0	746	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1492	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	746	50.0%
0	746	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1492	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	746	50.0%
0	746	50.0%

player_of_match
Categorical

HIGH CARDINALITY

Distinct	223
Distinct (%)	30.1%
Missing	4
Missing (%)	0.5%
Memory size	6.0 KiB

CH Gayle	21
AB de Villiers	20
MS Dhoni	17
RG Sharma	17
DA Warner	17
Other values (218)	650

Length

Max length	17
Median length	9
Mean length	9.455525606
Min length	5

Characters and Unicode

Total characters	7016
Distinct characters	53
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	94 ?
Unique (%)	12.7%

Sample

1st row	A Kumble
2nd row	DA Warner
3rd row	SM Pollock
4th row	AB de Villiers
5th row	DE Bollinger

Common Values

Value	Count	Frequency (%)
CH Gayle	21	2.8%
AB de Villiers	20	2.7%
MS Dhoni	17	2.3%
RG Sharma	17	2.3%
DA Warner	17	2.3%
YK Pathan	16	2.1%
SR Watson	15	2.0%
SK Raina	14	1.9%
G Gambhir	13	1.7%
V Kohli	12	1.6%
Other values (213)	580	77.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
sharma	29	1.9%
a	25	1.7%
sr	23	1.5%
de	23	1.5%
ch	23	1.5%
v	23	1.5%
ab	22	1.5%
gayle	21	1.4%
da	20	1.3%
singh	20	1.3%
Other values (344)	1285	84.9%

Most occurring characters

Value	Count	Frequency (%)
	772	11.0%
a	772	11.0%
e	339	4.8%
n	336	4.8%
r	325	4.6%
i	323	4.6%
h	315	4.5%
l	298	4.2%
S	274	3.9%
s	203	2.9%
Other values (43)	3059	43.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4128	58.8%
Uppercase Letter	2112	30.1%
Space Separator	772	11.0%
Dash Punctuation	4	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	772	18.7%
e	339	8.2%
n	336	8.1%
r	325	7.9%
i	323	7.8%
h	315	7.6%
l	298	7.2%
s	203	4.9%
t	160	3.9%
o	159	3.9%
Other values (16)	898	21.8%

Uppercase Letter

Value	Count	Frequency (%)
S	274	13.0%
A	191	9.0%
M	186	8.8%
R	172	8.1%
K	158	7.5%
P	142	6.7%
D	124	5.9%
J	106	5.0%
G	100	4.7%
H	99	4.7%
Other values (15)	560	26.5%

Space Separator

Value	Count	Frequency (%)
	772	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6240	88.9%
Common	776	11.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	772	12.4%
e	339	5.4%
n	336	5.4%
r	325	5.2%
i	323	5.2%
h	315	5.0%
l	298	4.8%
S	274	4.4%
s	203	3.3%
A	191	3.1%
Other values (41)	2864	45.9%

Common

Value	Count	Frequency (%)
	772	99.5%
-	4	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7016	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	772	11.0%
a	772	11.0%
e	339	4.8%
n	336	4.8%
r	325	4.6%
i	323	4.6%
h	315	4.5%
l	298	4.2%
S	274	3.9%
s	203	2.9%
Other values (43)	3059	43.6%

venue
Categorical

HIGH CORRELATION

Distinct	36
Distinct (%)	4.8%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

Eden Gardens	77
Feroz Shah Kotla	73
Wankhede Stadium	71
M Chinnaswamy Stadium	66
Rajiv Gandhi International Stadium, Uppal	63
Other values (31)	396

Length

Max length	52
Median length	21
Mean length	24.98257373
Min length	8

Characters and Unicode

Total characters	18637
Distinct characters	53
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Dr DY Patil Sports Academy
2nd row	Feroz Shah Kotla
3rd row	Wankhede Stadium
4th row	Maharashtra Cricket Association Stadium
5th row	Dr DY Patil Sports Academy

Common Values

Value	Count	Frequency (%)
Eden Gardens	77	10.3%
Feroz Shah Kotla	73	9.8%
Wankhede Stadium	71	9.5%
M Chinnaswamy Stadium	66	8.8%
Rajiv Gandhi International Stadium, Uppal	63	8.4%
MA Chidambaram Stadium, Chepauk	56	7.5%
Sawai Mansingh Stadium	47	6.3%
Punjab Cricket Association Stadium, Mohali	35	4.7%
Maharashtra Cricket Association Stadium	21	2.8%
Punjab Cricket Association IS Bindra Stadium, Mohali	19	2.5%
Other values (26)	218	29.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
stadium	526	20.9%
cricket	130	5.2%
association	97	3.9%
international	83	3.3%
eden	77	3.1%
gardens	77	3.1%
shah	73	2.9%
feroz	73	2.9%
kotla	73	2.9%
wankhede	71	2.8%
Other values (65)	1234	49.1%

Most occurring characters

Value	Count	Frequency (%)
a	2446	13.1%
	1768	9.5%
i	1435	7.7%
t	1127	6.0%
n	1021	5.5%
d	998	5.4%
e	862	4.6%
S	812	4.4%
r	781	4.2%
m	771	4.1%
Other values (43)	6616	35.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	13884	74.5%
Uppercase Letter	2733	14.7%
Space Separator	1768	9.5%
Other Punctuation	241	1.3%
Dash Punctuation	11	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	2446	17.6%
i	1435	10.3%
t	1127	8.1%
n	1021	7.4%
d	998	7.2%
e	862	6.2%
r	781	5.6%
m	771	5.6%
h	725	5.2%
u	703	5.1%
Other values (15)	3015	21.7%

Uppercase Letter

Value	Count	Frequency (%)
S	812	29.7%
C	357	13.1%
M	269	9.8%
A	210	7.7%
G	151	5.5%
P	118	4.3%
R	102	3.7%
I	102	3.7%
K	88	3.2%
W	79	2.9%
Other values (13)	445	16.3%

Other Punctuation

Value	Count	Frequency (%)
,	188	78.0%
.	46	19.1%
'	7	2.9%

Space Separator

Value	Count	Frequency (%)
	1768	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	11	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	16617	89.2%
Common	2020	10.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	2446	14.7%
i	1435	8.6%
t	1127	6.8%
n	1021	6.1%
d	998	6.0%
e	862	5.2%
S	812	4.9%
r	781	4.7%
m	771	4.6%
h	725	4.4%
Other values (38)	5639	33.9%

Common

Value	Count	Frequency (%)
	1768	87.5%
,	188	9.3%
.	46	2.3%
-	11	0.5%
'	7	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	18637	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	2446	13.1%
	1768	9.5%
i	1435	7.7%
t	1127	6.0%
n	1021	5.5%
d	998	5.4%
e	862	4.6%
S	812	4.4%
r	781	4.2%
m	771	4.1%
Other values (43)	6616	35.5%

umpire1
Categorical

HIGH CORRELATION

Distinct	49
Distinct (%)	6.6%
Missing	1
Missing (%)	0.1%
Memory size	6.0 KiB

HDPK Dharmasena	78
Asad Rauf	51
AK Chaudhary	47
M Erasmus	40
Aleem Dar	38
Other values (44)	491

Length

Max length	21
Median length	10
Mean length	10.66845638
Min length	5

Characters and Unicode

Total characters	7948
Distinct characters	47
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	0.4%

Sample

1st row	RE Koertzen
2nd row	SS Hazare
3rd row	BR Doctrove
4th row	CB Gaffaney
5th row	BR Doctrove

Common Values

Value	Count	Frequency (%)
HDPK Dharmasena	78	10.5%
Asad Rauf	51	6.8%
AK Chaudhary	47	6.3%
M Erasmus	40	5.4%
Aleem Dar	38	5.1%
BF Bowden	37	5.0%
S Ravi	36	4.8%
BR Doctrove	34	4.6%
AY Dandekar	24	3.2%
KN Ananthapadmanabhan	23	3.1%
Other values (39)	337	45.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
hdpk	78	5.2%
dharmasena	78	5.2%
s	65	4.3%
rauf	51	3.4%
asad	51	3.4%
ak	47	3.1%
chaudhary	47	3.1%
erasmus	40	2.7%
m	40	2.7%
dar	38	2.5%
Other values (83)	968	64.4%

Most occurring characters

Value	Count	Frequency (%)
a	1006	12.7%
	758	9.5%
n	519	6.5%
e	498	6.3%
r	448	5.6%
h	319	4.0%
D	310	3.9%
s	297	3.7%
d	272	3.4%
A	251	3.2%
Other values (37)	3270	41.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5020	63.2%
Uppercase Letter	2170	27.3%
Space Separator	758	9.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1006	20.0%
n	519	10.3%
e	498	9.9%
r	448	8.9%
h	319	6.4%
s	297	5.9%
d	272	5.4%
o	237	4.7%
m	201	4.0%
u	184	3.7%
Other values (14)	1039	20.7%

Uppercase Letter

Value	Count	Frequency (%)
D	310	14.3%
A	251	11.6%
K	239	11.0%
B	189	8.7%
R	180	8.3%
S	128	5.9%
C	119	5.5%
H	115	5.3%
N	92	4.2%
J	87	4.0%
Other values (12)	460	21.2%

Space Separator

Value	Count	Frequency (%)
	758	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7190	90.5%
Common	758	9.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1006	14.0%
n	519	7.2%
e	498	6.9%
r	448	6.2%
h	319	4.4%
D	310	4.3%
s	297	4.1%
d	272	3.8%
A	251	3.5%
K	239	3.3%
Other values (36)	3031	42.2%

Common

Value	Count	Frequency (%)
	758	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7948	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1006	12.7%
	758	9.5%
n	519	6.5%
e	498	6.3%
r	448	5.6%
h	319	4.0%
D	310	3.9%
s	297	3.7%
d	272	3.4%
A	251	3.2%
Other values (37)	3270	41.1%

umpire2
Categorical

HIGH CORRELATION

Distinct	48
Distinct (%)	6.4%
Missing	1
Missing (%)	0.1%
Memory size	6.0 KiB

S Ravi	68
C Shamshuddin	56
SJA Taufel	54
CK Nandan	48
RJ Tucker	41
Other values (43)	478

Length

Max length	15
Median length	10
Mean length	10.02281879
Min length	5

Characters and Unicode

Total characters	7467
Distinct characters	48
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	0.7%

Sample

1st row	SJA Taufel
2nd row	SJA Taufel
3rd row	DJ Harper
4th row	VK Sharma
5th row	RB Tiffin

Common Values

Value	Count	Frequency (%)
S Ravi	68	9.1%
C Shamshuddin	56	7.5%
SJA Taufel	54	7.2%
CK Nandan	48	6.4%
RJ Tucker	41	5.5%
BNJ Oxenford	31	4.2%
RB Tiffin	30	4.0%
VA Kulkarni	29	3.9%
AK Chaudhary	29	3.9%
Nitin Menon	27	3.6%
Other values (38)	332	44.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
s	84	5.6%
ravi	68	4.5%
shamshuddin	56	3.7%
c	56	3.7%
taufel	54	3.6%
sja	54	3.6%
ck	48	3.2%
nandan	48	3.2%
tucker	41	2.7%
rj	41	2.7%
Other values (78)	951	63.4%

Most occurring characters

Value	Count	Frequency (%)
a	771	10.3%
	756	10.1%
n	473	6.3%
r	415	5.6%
e	373	5.0%
i	370	5.0%
S	321	4.3%
h	310	4.2%
u	251	3.4%
d	245	3.3%
Other values (38)	3182	42.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4593	61.5%
Uppercase Letter	2118	28.4%
Space Separator	756	10.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	771	16.8%
n	473	10.3%
r	415	9.0%
e	373	8.1%
i	370	8.1%
h	310	6.7%
u	251	5.5%
d	245	5.3%
f	183	4.0%
s	180	3.9%
Other values (15)	1022	22.3%

Uppercase Letter

Value	Count	Frequency (%)
S	321	15.2%
K	228	10.8%
R	196	9.3%
A	181	8.5%
J	172	8.1%
T	156	7.4%
C	150	7.1%
N	133	6.3%
B	90	4.2%
M	77	3.6%
Other values (12)	414	19.5%

Space Separator

Value	Count	Frequency (%)
	756	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6711	89.9%
Common	756	10.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	771	11.5%
n	473	7.0%
r	415	6.2%
e	373	5.6%
i	370	5.5%
S	321	4.8%
h	310	4.6%
u	251	3.7%
d	245	3.7%
K	228	3.4%
Other values (37)	2954	44.0%

Common

Value	Count	Frequency (%)
	756	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7467	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	771	10.3%
	756	10.1%
n	473	6.3%
r	415	5.6%
e	373	5.0%
i	370	5.0%
S	321	4.3%
h	310	4.2%
u	251	3.4%
d	245	3.3%
Other values (38)	3182	42.6%

umpire3
Categorical

MISSING
UNIFORM

Distinct	2
Distinct (%)	100.0%
Missing	744
Missing (%)	99.7%
Memory size	6.0 KiB

S Ravi	1
A Chaudary	1

Length

Max length	10
Median length	8
Mean length	8
Min length	6

Characters and Unicode

Total characters	16
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	100.0%

Sample

1st row	A Chaudary
2nd row	S Ravi

Common Values

Value	Count	Frequency (%)
S Ravi	1	0.1%
A Chaudary	1	0.1%
(Missing)	744	99.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
s	1	25.0%
chaudary	1	25.0%
a	1	25.0%
ravi	1	25.0%

Most occurring characters

Value	Count	Frequency (%)
a	3	18.8%
	2	12.5%
A	1	6.2%
C	1	6.2%
h	1	6.2%
u	1	6.2%
d	1	6.2%
r	1	6.2%
y	1	6.2%
S	1	6.2%
Other values (3)	3	18.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10	62.5%
Uppercase Letter	4	25.0%
Space Separator	2	12.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	3	30.0%
h	1	10.0%
u	1	10.0%
d	1	10.0%
r	1	10.0%
y	1	10.0%
v	1	10.0%
i	1	10.0%

Uppercase Letter

Value	Count	Frequency (%)
A	1	25.0%
C	1	25.0%
S	1	25.0%
R	1	25.0%

Space Separator

Value	Count	Frequency (%)
	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	14	87.5%
Common	2	12.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	3	21.4%
A	1	7.1%
C	1	7.1%
h	1	7.1%
u	1	7.1%
d	1	7.1%
r	1	7.1%
y	1	7.1%
S	1	7.1%
R	1	7.1%
Other values (2)	2	14.3%

Common

Value	Count	Frequency (%)
	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	16	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	3	18.8%
	2	12.5%
A	1	6.2%
C	1	6.2%
h	1	6.2%
u	1	6.2%
d	1	6.2%
r	1	6.2%
y	1	6.2%
S	1	6.2%
Other values (3)	3	18.8%

first_bat_team
Categorical

HIGH CORRELATION

Distinct	15
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

Mumbai Indians	99
Kings XI Punjab	90
Chennai Super Kings	87
Royal Challengers Bangalore	85
Kolkata Knight Riders	82
Other values (10)	303

Length

Max length	27
Median length	16
Mean length	17.97184987
Min length	13

Characters and Unicode

Total characters	13407
Distinct characters	37
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Deccan Chargers
2nd row	Delhi Daredevils
3rd row	Kolkata Knight Riders
4th row	Royal Challengers Bangalore
5th row	Chennai Super Kings

Common Values

Value	Count	Frequency (%)
Mumbai Indians	99	13.3%
Kings XI Punjab	90	12.1%
Chennai Super Kings	87	11.7%
Royal Challengers Bangalore	85	11.4%
Kolkata Knight Riders	82	11.0%
Delhi Daredevils	72	9.7%
Rajasthan Royals	66	8.8%
Sunrisers Hyderabad	61	8.2%
Deccan Chargers	43	5.8%
Pune Warriors	20	2.7%
Other values (5)	41	5.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kings	177	9.5%
indians	99	5.3%
mumbai	99	5.3%
xi	90	4.8%
punjab	90	4.8%
super	87	4.7%
chennai	87	4.7%
challengers	85	4.6%
bangalore	85	4.6%
royal	85	4.6%
Other values (22)	874	47.0%

Most occurring characters

Value	Count	Frequency (%)
a	1510	11.3%
n	1140	8.5%
	1112	8.3%
e	1004	7.5%
i	927	6.9%
s	887	6.6%
r	783	5.8%
l	649	4.8%
g	502	3.7%
h	447	3.3%
Other values (27)	4446	33.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10347	77.2%
Uppercase Letter	1948	14.5%
Space Separator	1112	8.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1510	14.6%
n	1140	11.0%
e	1004	9.7%
i	927	9.0%
s	887	8.6%
r	783	7.6%
l	649	6.3%
g	502	4.9%
h	447	4.3%
u	408	3.9%
Other values (11)	2090	20.2%

Uppercase Letter

Value	Count	Frequency (%)
K	355	18.2%
R	314	16.1%
C	220	11.3%
D	192	9.9%
I	189	9.7%
S	163	8.4%
P	125	6.4%
M	99	5.1%
X	90	4.6%
B	85	4.4%
Other values (5)	116	6.0%

Space Separator

Value	Count	Frequency (%)
	1112	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12295	91.7%
Common	1112	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1510	12.3%
n	1140	9.3%
e	1004	8.2%
i	927	7.5%
s	887	7.2%
r	783	6.4%
l	649	5.3%
g	502	4.1%
h	447	3.6%
u	408	3.3%
Other values (26)	4038	32.8%

Common

Value	Count	Frequency (%)
	1112	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13407	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1510	11.3%
n	1140	8.5%
	1112	8.3%
e	1004	7.5%
i	927	6.9%
s	887	6.6%
r	783	5.8%
l	649	4.8%
g	502	3.7%
h	447	3.3%
Other values (27)	4446	33.2%

first_bowl_team
Categorical

HIGH CORRELATION

Distinct	15
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	6.0 KiB

Royal Challengers Bangalore	94
Kolkata Knight Riders	94
Delhi Daredevils	89
Mumbai Indians	84
Kings XI Punjab	84
Other values (10)	301

Length

Max length	27
Median length	16
Mean length	18.08310992
Min length	13

Characters and Unicode

Total characters	13490
Distinct characters	37
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Royal Challengers Bangalore
2nd row	Kolkata Knight Riders
3rd row	Mumbai Indians
4th row	Rising Pune Supergiants
5th row	Deccan Chargers

Common Values

Value	Count	Frequency (%)
Royal Challengers Bangalore	94	12.6%
Kolkata Knight Riders	94	12.6%
Delhi Daredevils	89	11.9%
Mumbai Indians	84	11.3%
Kings XI Punjab	84	11.3%
Rajasthan Royals	80	10.7%
Chennai Super Kings	73	9.8%
Sunrisers Hyderabad	44	5.9%
Deccan Chargers	32	4.3%
Pune Warriors	26	3.5%
Other values (5)	46	6.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kings	157	8.4%
delhi	97	5.2%
bangalore	94	5.1%
riders	94	5.1%
kolkata	94	5.1%
challengers	94	5.1%
knight	94	5.1%
royal	94	5.1%
daredevils	89	4.8%
xi	84	4.5%
Other values (22)	868	46.7%

Most occurring characters

Value	Count	Frequency (%)
a	1553	11.5%
	1113	8.3%
n	1080	8.0%
e	1019	7.6%
i	918	6.8%
s	884	6.6%
r	763	5.7%
l	751	5.6%
g	501	3.7%
h	477	3.5%
Other values (27)	4431	32.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10434	77.3%
Uppercase Letter	1943	14.4%
Space Separator	1113	8.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1553	14.9%
n	1080	10.4%
e	1019	9.8%
i	918	8.8%
s	884	8.5%
r	763	7.3%
l	751	7.2%
g	501	4.8%
h	477	4.6%
o	411	3.9%
Other values (11)	2077	19.9%

Uppercase Letter

Value	Count	Frequency (%)
R	363	18.7%
K	359	18.5%
D	218	11.2%
C	207	10.7%
I	168	8.6%
S	132	6.8%
P	125	6.4%
B	94	4.8%
M	84	4.3%
X	84	4.3%
Other values (5)	109	5.6%

Space Separator

Value	Count	Frequency (%)
	1113	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12377	91.7%
Common	1113	8.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1553	12.5%
n	1080	8.7%
e	1019	8.2%
i	918	7.4%
s	884	7.1%
r	763	6.2%
l	751	6.1%
g	501	4.0%
h	477	3.9%
o	411	3.3%
Other values (26)	4020	32.5%

Common

Value	Count	Frequency (%)
	1113	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13490	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	1553	11.5%
	1113	8.3%
n	1080	8.0%
e	1019	7.6%
i	918	6.8%
s	884	6.6%
r	763	5.7%
l	751	5.6%
g	501	3.7%
h	477	3.5%
Other values (27)	4431	32.8%

first_bat_score
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	148
Distinct (%)	19.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	161.3565684

Minimum	56
Maximum	263
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.0 KiB

Quantile statistics

Minimum	56
5-th percentile	111
Q1	142
median	163
Q3	182
95-th percentile	209.75
Maximum	263
Range	207
Interquartile range (IQR)	40

Descriptive statistics

Standard deviation	30.53784434
Coefficient of variation (CV)	0.1892569026
Kurtosis	0.4992793235
Mean	161.3565684
Median Absolute Deviation (MAD)	20
Skewness	-0.200546894
Sum	120372
Variance	932.5599367
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
187	16	2.1%
165	15	2.0%
160	14	1.9%
178	14	1.9%
168	14	1.9%
163	14	1.9%
164	13	1.7%
183	12	1.6%
161	12	1.6%
148	12	1.6%
Other values (138)	610	81.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
56	1	0.1%
62	1	0.1%
67	2	0.3%
70	2	0.3%
73	1	0.1%
80	1	0.1%
81	1	0.1%
82	1	0.1%
88	1	0.1%
89	1	0.1%

Value	Count	Frequency (%)
263	1	0.1%
248	1	0.1%
246	1	0.1%
245	1	0.1%
240	1	0.1%
235	1	0.1%
232	2	0.3%
231	3	0.4%
230	1	0.1%
227	1	0.1%

second_bat_score
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	143
Distinct (%)	19.2%
Missing	2
Missing (%)	0.3%
Infinite	0
Infinite (%)	0.0%
Mean	147.8413978

Minimum	2
Maximum	223
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.0 KiB

Quantile statistics

Minimum	2
5-th percentile	92
Q1	131
median	150
Q3	169
95-th percentile	194
Maximum	223
Range	221
Interquartile range (IQR)	38

Descriptive statistics

Standard deviation	31.15340597
Coefficient of variation (CV)	0.2107218034
Kurtosis	0.9115891677
Mean	147.8413978
Median Absolute Deviation (MAD)	19
Skewness	-0.6126276321
Sum	109994
Variance	970.5347038
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
164	14	1.9%
161	14	1.9%
146	14	1.9%
162	14	1.9%
142	13	1.7%
160	13	1.7%
159	13	1.7%
150	13	1.7%
137	12	1.6%
153	11	1.5%
Other values (133)	613	82.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	1	0.1%
41	1	0.1%
44	1	0.1%
48	1	0.1%
49	1	0.1%
55	1	0.1%
58	2	0.3%
60	1	0.1%
61	1	0.1%
66	2	0.3%

Value	Count	Frequency (%)
223	2	0.3%
217	1	0.1%
214	2	0.3%
211	1	0.1%
208	2	0.3%
207	2	0.3%
206	2	0.3%
205	1	0.1%
204	3	0.4%
203	1	0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	id	season	city	date	team1	team2	toss_winner	toss_decision	winner	eliminator	dl_applied	win_by_runs	win_by_wickets	result	overs	player_of_match	venue	umpire1	umpire2	umpire3	first_bat_team	first_bowl_team	first_bat_score	second_bat_score
0	419164	2010	Mumbai	2010-04-24	Royal Challengers Bangalore	Deccan Chargers	Deccan Chargers	bat	Royal Challengers Bangalore	NaN	NaN	NaN	9.0	NaN	20	A Kumble	Dr DY Patil Sports Academy	RE Koertzen	SJA Taufel	NaN	Deccan Chargers	Royal Challengers Bangalore	82.0	86.0
1	419131	2010	Delhi	2010-03-29	Delhi Daredevils	Kolkata Knight Riders	Delhi Daredevils	bat	Delhi Daredevils	NaN	NaN	40.0	NaN	NaN	20	DA Warner	Feroz Shah Kotla	SS Hazare	SJA Taufel	NaN	Delhi Daredevils	Kolkata Knight Riders	177.0	137.0
2	336021	2008	Mumbai	2008-05-16	Mumbai Indians	Kolkata Knight Riders	Mumbai Indians	field	Mumbai Indians	NaN	NaN	NaN	8.0	NaN	20	SM Pollock	Wankhede Stadium	BR Doctrove	DJ Harper	NaN	Kolkata Knight Riders	Mumbai Indians	67.0	68.0
3	980931	2016	Pune	2016-04-22	Rising Pune Supergiants	Royal Challengers Bangalore	Rising Pune Supergiants	field	Royal Challengers Bangalore	NaN	NaN	13.0	NaN	NaN	20	AB de Villiers	Maharashtra Cricket Association Stadium	CB Gaffaney	VK Sharma	NaN	Royal Challengers Bangalore	Rising Pune Supergiants	185.0	172.0
4	419163	2010	Mumbai	2010-04-22	Chennai Super Kings	Deccan Chargers	Chennai Super Kings	bat	Chennai Super Kings	NaN	NaN	38.0	NaN	NaN	20	DE Bollinger	Dr DY Patil Sports Academy	BR Doctrove	RB Tiffin	NaN	Chennai Super Kings	Deccan Chargers	142.0	104.0
5	419136	2010	Chandigarh	2010-04-02	Kings XI Punjab	Royal Challengers Bangalore	Kings XI Punjab	bat	Royal Challengers Bangalore	NaN	NaN	NaN	6.0	NaN	20	KP Pietersen	Punjab Cricket Association Stadium, Mohali	BF Bowden	M Erasmus	NaN	Kings XI Punjab	Royal Challengers Bangalore	181.0	184.0
6	336026	2008	Bangalore	2008-05-19	Royal Challengers Bangalore	Delhi Daredevils	Delhi Daredevils	field	Delhi Daredevils	NaN	NaN	NaN	5.0	NaN	20	SP Goswami	M Chinnaswamy Stadium	SJ Davis	GA Pratapkumar	NaN	Royal Challengers Bangalore	Delhi Daredevils	154.0	158.0
7	980963	2016	Kolkata	2016-05-04	Kolkata Knight Riders	Kings XI Punjab	Kings XI Punjab	field	Kolkata Knight Riders	NaN	NaN	7.0	NaN	NaN	20	AD Russell	Eden Gardens	AK Chaudhary	HDPK Dharmasena	NaN	Kolkata Knight Riders	Kings XI Punjab	164.0	157.0
8	501236	2011	Chennai	2011-05-01	Chennai Super Kings	Deccan Chargers	Chennai Super Kings	bat	Chennai Super Kings	NaN	NaN	19.0	NaN	NaN	20	JA Morkel	MA Chidambaram Stadium, Chepauk	Aleem Dar	RB Tiffin	NaN	Chennai Super Kings	Deccan Chargers	165.0	146.0
9	501263	2011	Mumbai	2011-05-20	Mumbai Indians	Rajasthan Royals	Mumbai Indians	bat	Rajasthan Royals	NaN	NaN	NaN	10.0	NaN	20	SR Watson	Wankhede Stadium	RE Koertzen	PR Reiffel	NaN	Mumbai Indians	Rajasthan Royals	133.0	134.0

Last rows

	id	season	city	date	team1	team2	toss_winner	toss_decision	winner	eliminator	dl_applied	win_by_runs	win_by_wickets	result	overs	player_of_match	venue	umpire1	umpire2	umpire3	first_bat_team	first_bowl_team	first_bat_score	second_bat_score
736	336015	2008	Jaipur	2008-05-11	Rajasthan Royals	Delhi Daredevils	Rajasthan Royals	field	Rajasthan Royals	NaN	NaN	NaN	3.0	NaN	20	SR Watson	Sawai Mansingh Stadium	SJ Davis	RE Koertzen	NaN	Delhi Daredevils	Rajasthan Royals	156.0	159.0
737	419150	2010	Jaipur	2010-04-11	Rajasthan Royals	Mumbai Indians	Rajasthan Royals	field	Mumbai Indians	NaN	NaN	37.0	NaN	NaN	20	SR Tendulkar	Sawai Mansingh Stadium	BR Doctrove	SK Tarapore	NaN	Mumbai Indians	Rajasthan Royals	174.0	137.0
738	980957	2016	Pune	2016-05-01	Rising Pune Supergiants	Mumbai Indians	Mumbai Indians	field	Mumbai Indians	NaN	NaN	NaN	8.0	NaN	20	RG Sharma	Maharashtra Cricket Association Stadium	AY Dandekar	RJ Tucker	NaN	Rising Pune Supergiants	Mumbai Indians	159.0	161.0
739	1136598	2018	Indore	2018-05-06	Kings XI Punjab	Rajasthan Royals	Kings XI Punjab	field	Kings XI Punjab	NaN	NaN	NaN	6.0	NaN	20	Mujeeb Ur Rahman	Holkar Cricket Stadium	C Shamshuddin	S Ravi	NaN	Rajasthan Royals	Kings XI Punjab	152.0	155.0
740	981009	2016	Kolkata	2016-05-22	Kolkata Knight Riders	Sunrisers Hyderabad	Sunrisers Hyderabad	field	Kolkata Knight Riders	NaN	NaN	22.0	NaN	NaN	20	YK Pathan	Eden Gardens	KN Ananthapadmanabhan	M Erasmus	NaN	Kolkata Knight Riders	Sunrisers Hyderabad	171.0	149.0
741	1136567	2018	Hyderabad	2018-04-12	Sunrisers Hyderabad	Mumbai Indians	Sunrisers Hyderabad	field	Sunrisers Hyderabad	NaN	NaN	NaN	1.0	NaN	20	Rashid Khan	Rajiv Gandhi International Stadium, Uppal	NJ Llong	CK Nandan	NaN	Mumbai Indians	Sunrisers Hyderabad	147.0	151.0
742	392209	2009	East London	2009-05-04	Chennai Super Kings	Deccan Chargers	Chennai Super Kings	bat	Chennai Super Kings	NaN	NaN	78.0	NaN	NaN	20	MS Dhoni	Buffalo Park	BR Doctrove	M Erasmus	NaN	Chennai Super Kings	Deccan Chargers	178.0	100.0
743	336012	2008	Bangalore	2008-05-28	Royal Challengers Bangalore	Mumbai Indians	Mumbai Indians	field	Mumbai Indians	NaN	NaN	NaN	9.0	NaN	20	CRD Fernando	M Chinnaswamy Stadium	BF Bowden	AV Jayaprakash	NaN	Royal Challengers Bangalore	Mumbai Indians	122.0	126.0
744	729313	2014	NaN	2014-04-28	Kings XI Punjab	Royal Challengers Bangalore	Kings XI Punjab	field	Kings XI Punjab	NaN	NaN	NaN	5.0	NaN	20	Sandeep Sharma	Dubai International Cricket Stadium	BF Bowden	S Ravi	NaN	Royal Challengers Bangalore	Kings XI Punjab	124.0	127.0
745	419157	2010	Bangalore	2010-04-17	Royal Challengers Bangalore	Mumbai Indians	Royal Challengers Bangalore	field	Mumbai Indians	NaN	NaN	57.0	NaN	NaN	20	R McLaren	M Chinnaswamy Stadium	HDPK Dharmasena	SJA Taufel	NaN	Mumbai Indians	Royal Challengers Bangalore	191.0	134.0

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Dash Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories